Some embodiments described herein relate generally to systems for observation, and, in particular, to methods and apparatus for observing a system or process, such as for detecting anomalies and faults of the system or process, in substantially real-time.
Some known fault detection systems use predefined, static thresholds to detect abnormal behaviors in a system or process. Such known fault detection systems, however, are typically not applicable to detect anomalies for a dynamic system or process, and are unable to detect unknown types of system or process faults. Some other known fault detection systems use dynamic or adaptive thresholds to detect abnormal behaviors. Such known fault detection systems, however, typically do not distinguish improbable or unusual behavior (i.e., abnormality) from bad behavior (i.e., fault). Moreover, such known fault detection systems typically are computationally expensive, thus infeasible to operate on a large scale and in substantially real-time.
Accordingly, a need exists for methods and apparatus that 1) can dynamically and automatically detect anomalies, 2) can distinguish faults from abnormal behaviors, and 3) are computationally inexpensive and scalable.